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What Do Language Priors Contribute to Darcy-Flow Inversion? A Mechanistic Audit

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arXiv:2606. 24967v1 Announce Type: new Abstract: In ill-posed inverse problems, the recovered solution depends as much on the prior as on the data, yet much of the engineering knowledge that could serve as that prior is recorded qualitatively rather than in formal mathematical form.

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Authors: Taiga Saito, Yu Otake, Daijiro Mizutani, Sopheakpolin Mom
Released: 2026-06-25 (14d ago)
Topic: Related to current project
Relation to my work: Read next because What Do Language Priors Contribute to Darcy-Flow Inversion? A Mechanistic Audit overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, phrase, class, under, rate, compare, test, lora. Source: arxiv cs.LG (Machine Learning).
arXiv: 2606.24967

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